For our MCDropout model, we use an MLP with one hidden layer that contain 300 neurons. The activation function is ReLU and the dropout rate is \(0.5\) . The uncertainty is calculated via average entropy of 100 forward dropout. The network is optimised by Adam with a cross-entropy loss using the PyTorch library [1]}.
